A Study on the Apparent Randomness of a Wildlife Sample
Sampling is used to estimate characteristics of the population when we are unable to investigate the population as a whole. In an ideal world a sample would be a perfectly scaled-down version of the original population in the sense that every characteristic of the population would be matched in the sample. Although this ideal is almost impossible to meet, researchers aim to get as close to this as possible. Even though wildlife researchers are aware of the advantages of random sampling, these methods are usually not implemented. In practice, most samples are convenience samples, so the selection probabilities of the elements cannot be described, making it impossible to derive statistically valid estimators and their errors. Typically, it is assumed that these convenience samples approximate random samples so that inferences can be made about the population, however, these assumptions remain mostly unfounded and untested. In wildlife research, probability sampling methods such as simple random sampling (SRS) are not practical since all elements in the population may not be available or accessible. Instead, prior knowledge is often used to select elements, or in some cases, any available element is included. Only a small number of studies on this aspect have been done.
This paper will assess the impact of taking a convenience sample by making use of cattle livestock data. In this study, a convenience sample was obtained by selecting 10\% of the farmers registered at each of the dip tanks.В Census data is available for this population. We aim to provide measures of how the quality of the sample, in other words the randomness or nonrandomness of the sample, affects statistical analysis. We aim to show that a convenience sample obtained in this setting will yield less reliable results than a probability sample. We would like to add a measure attached to a convenience statistical analysis in order to make a comparison with the unknown statistical analysis attached to a true random sample.
The journal Biomath Communications is an open access journal. All published articles are immeditely available online and the respective DOI link activated. All articles can be access for free and no reader registration of any sort is required. No fees are charged to authors for article submission or processing. Online publications are funded through volunteer work, donations and grants.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License 4.0 that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).